Step 0: Import Libraries and load data from csv file created from EDA stage
Graph 1: Total Confirmed Cases By Date
Graph 2: Median Age of Total Confirmed Cases By Date
Graph 3: Daily Confirmed Cases by Age Groups
Graph 4: Daily Hospitalised Cases by Age Groups
Step 5: Create one new dataset for graphing the Percentage of Total Hospitalised Cases per Total Confirmed Cases by Age Groups
Graph 5: Percentage of Total Hospitalised Cases per Total Confirmed Cases by Age Groups
Step 6: Create a new dataset to show the relationship between Hospitalised Cases Percentage and Confirmed Cases Percentage in all Age Groups
Graph 6: Percentage of Hospitalised Cases and Confirmed Cases between all Age Groups
Conclusion
import pandas as pd
import numpy as np
import plotly.express as px
Covid_Tan = pd.read_csv("Covid_Tan.csv", parse_dates = ["StatisticsProfileDate"])
fig = px.line(Covid_Tan, x="StatisticsProfileDate", y = "Cases", color = "Age", title= "Total Confirmed Cases By Date",
labels={"StatisticsProfileDate": "Statistics Date", "Cases": "Total Confirmed Cases", "Age": "Age Group"}
)
fig.update_layout(title_font_color="#800000", title_x=0.5)
fig.show()
fig_median = px.line(Covid_Tan.head(660), x="StatisticsProfileDate", y = "Median_Age", title= "Median Age of Total Confirmed Cases By Date",
labels={"StatisticsProfileDate": "Statistics Date", "Median_Age": "Median Age"}
)
fig_median.update_layout(title_font_color="#800000", title_x=0.5)
fig_median.show()
fig = px.line(Covid_Tan, x="StatisticsProfileDate", y = "CaseByDay", color = "Age" , title= "Daily Confirmed Cases",
labels={"StatisticsProfileDate": "Statistics Date", "CaseByDay": "Confirmed Cases", "Age": "Age Group"}
)
fig.update_layout(title_font_color="#800000", title_x=0.5)
fig.show()
fig = px.line(Covid_Tan, x="StatisticsProfileDate", y = "HospitalCaseByDay", color = "Age" , title= "Daily Hospitalised Cases",
labels={"StatisticsProfileDate": "Statistics Date", "HospitalCaseByDay": "Hospitalised Cases", "Age": "Age Group"}
)
fig.update_layout(title_font_color="#800000", title_x=0.5)
fig.show()
Covid_Tan_max = Covid_Tan[Covid_Tan.StatisticsProfileDate == Covid_Tan.StatisticsProfileDate.max()].copy()
Covid_Tan_max["HospitalisedPercentagePerCase"] = Covid_Tan_max.HospitalisedCases * 100/Covid_Tan_max.Cases
fig = px.bar(Covid_Tan_max, x="HospitalisedPercentagePerCase", y = "Age", title= "Percentage of Total Hospitalised Cases per Total Confirmed Cases",
labels={"HospitalisedPercentagePerCase": "Percentage of Hospitalised Cases", "Age": "Age Group"}
)
fig.update_layout(title_font_color="#800000", title_x=0.5)
fig.show()
Covid_Tan_max["Hospitalised"] = Covid_Tan_max.HospitalisedCases * 100/Covid_Tan_max.HospitalisedCovidCases
Covid_Tan_max["Confirmed Cases"] = Covid_Tan_max.Cases * 100/Covid_Tan_max.CovidCasesConfirmed
Covid_Tan_new = Covid_Tan_max.loc[:,["Age","Confirmed Cases","Hospitalised"]].copy()
Covid_Tan_new_melt = pd.melt(Covid_Tan_new, id_vars="Age",value_name="Percentage %",var_name="Type")
fig = px.bar(Covid_Tan_new_melt, x="Percentage %", y = "Age", color = "Type", barmode = "group", title= "Percentage of Hospitalised Cases and Confirmed Cases by Age Groups",
labels={"Type": "", "Age": "Age Group"}
)
fig.update_layout(title_font_color="#800000", title_x=0.5)
fig.show()